The error you're encountering (OperationalError: TExecuteStatementResp(status=TStatus(statusCode=3, ...) indicates that there was an issue during the execution of the Hive query. The specific error message within the response is Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.tez.TezTask. Here are a few steps you can take to troubleshoot and resolve the issue: Check Hive Query Logs: Review the Hive query logs to get more details about the error. The logs might provide information about the specific query or task that failed, including any error messages or stack traces. You can find the logs in the Hive logs directory. The location may vary based on your Hadoop distribution and configuration. Inspect Query Syntax: Double-check the syntax of your Hive SQL query. Ensure that the query is valid and properly formed. Sometimes, a syntax error can lead to execution failures. Verify Hive Table Existence: Confirm that the Hive table you're querying actually exists. If the table or the specified database is missing, it can lead to errors. Check Permissions: Verify that the user running the Python query has the necessary permissions to access and query the Hive table. Lack of permissions can result in execution errors. Examine Tez Configuration: If your Hive queries use the Tez execution engine, check the Tez configuration. Ensure that Tez is properly configured on your cluster and that there are no issues with the Tez execution. Look for Resource Constraints: The error message mentions TezTask, so consider checking if there are any resource constraints on the Tez execution, such as memory or container size limitations. Update Python Library: Ensure that you are using a compatible version of the Python library for interacting with Hive (e.g., pyhive or pyhive[hive]). Updating the library to the latest version might help resolve certain issues. Test with a Simple Query: Simplify your query to a basic one and see if it executes successfully. This can help isolate whether the issue is specific to the query or a more general problem. After reviewing the logs and checking the mentioned aspects, you should have more insights into what might be causing the error. If the issue persists, consider providing more details about the Hive query and the surrounding context, so we can offer more targeted assistance. ... View more

The error message indicates that there is an issue related to resource allocation in YARN, the resource manager in Hadoop. Specifically, the error mentions that the requested resource exceeds the maximum allowed allocation. Here are some steps you can take to address this issue: Review YARN Configuration: Check the YARN configuration settings, particularly those related to resource allocation. Look for properties such as yarn.scheduler.maximum-allocation-mb and yarn.scheduler.maximum-allocation-vcores. Ensure that the values configured for these properties are sufficient for the resources needed by HiveServer2. Increase Maximum Allocation: If the error persists, you might need to increase the maximum allocation for memory and vCores in the YARN scheduler configuration. Update the yarn.scheduler.maximum-allocation-mb and yarn.scheduler.maximum-allocation-vcores properties in the YARN configuration files. Check NodeManager Resources: Verify the resources available on the NodeManagers in your cluster. The maximum allowed allocation is calculated based on the maximum resources of registered NodeManagers. If the NodeManagers have sufficient resources, you can adjust the YARN configuration accordingly. Monitor Resource Usage: Monitor the resource usage in your YARN cluster using tools like the ResourceManager UI or the YARN command-line tools (yarn top, yarn node -list -all, etc.). Identify any patterns of resource exhaustion or contention that could be causing the issue. Review Hive Configuration: Review the Hive configurations related to resource allocation, such as hive.tez.container.size and other relevant settings. Ensure that they are appropriately configured for your cluster. After making any configuration changes, restart the affected services (YARN, HiveServer2) for the changes to take effect.  ... View more

Hello @Ayuuu  Can you share the stack trace of the error ... View more

@larnone  As this is an older post, we recommend starting a new thread. The new thread will provide the opportunity to provide details specific to your environment that could aid others in providing a more accurate answer to your question. ... View more

Welcome to the community @Ryand2. I hope @Ayuuu has helped you identify the issue here. If so, please use the accept as solution button to mark his reply as the answer. ... View more

Hello Vidya, would you support me in this as well?   regards, Mahrous Badr ... View more

I do not want to be harsh, but I do not know better ways to show my disappointment with your support. All I wanted was to locate VMs for use with training and you failed on multiple occasions to point me to the site.    Instead, I get links with limited explanations, or replied asking me if the problem was solved with no prior attempts to answer the questions. I did get that the training was relevant, but that was it and all that I now expect. I have no confidence that those who replied even checked the information about which I inquired.   If there is not time to answer the question, then do not answer the question with half hearted responses. I looks bad for a company I once had interest  and thought well of.  You can mark this closed and unresolved as you have not answered the question and I no longer care to hear from your support team.  I have wasted enough time for what should be a simple answer. ... View more

@uday123 Has the reply helped resolve your issue? If so, please mark the appropriate reply as the solution, as it will make it easier for others to find the answer in the future. Thanks. ... View more

Welcome to the community @RickJ . While you wait for someone more knowledgable to respond, I would like to point out something in case it gets you closer.  I see: skipping sourcing equivalent of /etc/default/hadoop due to missing CDH_VERSION Check to ensure that the CDH_VERSION variable is set to the correct value for the version of Cloudera Hadoop that you are trying to use. ... View more

Thank you for posting your findings @HanzalaShaikh  ... View more